Research Article
Gaussian Quantum Bat Algorithm with Direction of Mean Best Position for Numerical Function Optimization
Algorithm 3
Pseudocode of the GQMBA algorithm.
| Initialize the bat population and ; | | Define pulse frequency , pulse rate and the loudness ; | | while do | | for to n do | | Generate new solutions by calculating the distance between the bat and current global best position, updating positions using equations (8) and (14); | | if then | | if then | | Bats fly with quantum behavior and positions using equations (10), (11) and (15); | | else | | The mean best position is used to guide other bats and position updated using equations (11) and (16); | | end if | | end if | | if then | | Accept the new solutions; | | Increase and reduce using equations (5) and (6); | | end if | | Rank the bats and find the current best ; | | end for | | ; | | end while |
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